6/01/2009 @ 6:00AM

IT's Role In The Recession

Information technology experts didn’t cause the current economic downturn, but they certainly made it worse.

The creation of incredibly complex risk models on Wall Street by pedigreed quantitative analysts, or quants, and the almost total reliance by trading houses on those models turned what could have been just another housing bubble into a global disaster. Forbes caught up with David Moschella, global research director for Computer Science Corp.’s Leading Edge Forum, to talk about what went wrong and what’s changing.

Forbes: What is IT’s role in the recession?

David Moschella: If you look at the housing bubble and all the crazy things the banks did, supporting and enabling that were the computerized models. They spun out equations that said from a risk-management perspective this was OK. In particular, they used the Gaussian copula formula to calculate the risk of the credit fault swaps.

This is what all the “quants” were doing, right?

Yes. These were the best and brightest taking supercomputers, putting in complex equations and coming out with answers that said this really highly leveraged model that depended on house prices rising forever wasn’t all that risky. Now people are realizing those models had some serious flaws.

Why did it take so long?

Some people realized those equations had serious flaws from the beginning. But when things are going well people ignore those risks and make money while they can. These computers had a role in convincing people everything was OK. And obviously the top management in firms can’t understand these equations. They’re very complex. There are lots of variables, lots of equations, and they assumed they were OK. In the end, it gave them a very false sense of confidence.

So what role did IT actually play in bringing down the global economy?

It’s certainly not the main culprit. There have been many speculative bubbles. But IT played a role in providing reassurances, and it magnified the volumes and speed. Without computers you could never have the volumes of derivatives contracts, the complex hedging systems–90% of all trading now is algorithmic and done by machines. You could never have the volume and scale and speed without computers. That role is pretty important. It couldn’t happen without the housing bubble, but without computers it wouldn’t have been nearly as bad as it has been. These were the crown jewels of many of these financial organizations. Now they understand they couldn’t trust this stuff.

Is this limited to financial markets?

No, one of the lessons is you can’t fully trust any model. You need to have skepticism about it. Computer models, formulas and equations exist across many industries and sectors. There are lessons here beyond the financial industry. There are things you understand and things you don’t. And if you don’t fully understand it, you’re adding some serious risk.

How do we avoid this in the future?

Beware of geeks bearing formulas. You don’t throw them out. The Black-Scholes model has led to all sorts of problems, but it also has been used very productively. It’s not a question of throwing these formulas out. It’s a matter of being disciplined about where you use them. These are not universally applicable, and no one model is always right.

How did this slip past everyone?

These models are created by specialized mathematicians and physicists–the best and the brightest. There’s a 20-year culture on Wall Street that sophisticated modeling and these computer gurus were the future of that industry. For that time, they made that industry a great deal of money and were extremely well paid to do it. They built up significant credibility because for many years they appeared to be right. It appeared to be working. But there were always people in that field who could see the limitations of those formulas and that they wouldn’t hold up in all circumstances. When a formula falls apart because housing prices start going down, then it’s not really much of a formula.

Who hired these people? Was it the CIOs?

The CIOs were almost never involved. The IT people worked directly for the trading people in the banks. They would have relationships with the CIOs, but it was really a product IT. They worked directly with the traders. They were mostly mathematicians, economists and people who understood complex models and the systems behind them. They handle millions of equations and spit out recommendations.

So let’s go back to the role of technology in this downturn. Exactly how much responsibility does it have?

It didn’t cause the bubble, but it certainly spread it faster. Some of these companies would have 25,000 derivative contracts with 1,000 other companies. You can’t manage that as an individual, but for a computer that’s easy.

How are IT departments responding?

There’s no question that many of the banks are shrinking and reducing the role of those activities. The credit fault swap market has essentially vanished. Derivative trading is going to be regulated. All of that will diminish the roles of these people. There will still be people modeling things, but the role that computer models had will be very limited for the next few years.

So how do the mere mortals clean up this mess?

There’s still a strong role for information and information technology, but there will be a bigger role for human judgment about the quality of different investments. That’s a big change. People are looking at their portfolio and trying to make decisions on their own. From the CIO’s point of view, they can say, “These people didn’t work for me. They worked for the trading desk.” They’ll build applications, but they won’t go into the rocket science business.

So this is really the first “I Robot” disaster?

Yes. That’s a good way of looking at it. The popular culture has anticipated this in movies, and it’s not far from the truth.

Doesn’t it only get worse from here? Machines are still trading with machines?

Yes, but there’s machine trading based on things you understand and machine trading based on formulas that you can’t understand. Those are different. General reliance on complex, computerized trading is shrinking. It’s not the trading that’s the problem, it’s the decision making. If you look at what’s happening in the sector of leverage, they’re not going to bet 60-to-1 leverage. They’ll do 10-to-1. You can’t take that much risk. The computers said you could, but you can’t believe it.